Machine Learning with H2O Flow

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Machine Learning with H2O Flow H2O is a leading open-source machine learning and artificial intelligence platform trusted by data scientists and machine learning practitioners. It has APIs available in R, Python, Scala, and also a web-based point and click interface called Flow

In this Guided Project, you will:

Train and evaluate machine learning models with H2O Flow

Solve a business analytics problem using machine learning with Flow and AutoML

This is a hands-on, guided introduction to using H2O Flow for machine learning. By the end of this project, you will be able to train and evaluate machine learning models with H2O Flow and AutoML, without writing a single line of code! You will use the point and click, web-based interface to H2O called Flow to solve a business analytics problem with machine learning. H2O is a leading open-source machine learning and artificial intelligence platform trusted by data scientists and machine learning practitioners. It has APIs available in R, Python, Scala, and also a web-based point and click interface called Flow. H2O’s AutoML automates the process of training and tuning a large selection of models, allowing the user to focus on other aspects of the data science and machine learning pipelines such as data pre-processing, feature engineering, and model deployment. To get the most out of this project, we recommend that you have an understanding of basic machine learning theory, and have trained machine learning models. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

Introduction and Project Overview

Importing and Parsing Data

Creating Training and Test Splits

Build and Evaluate a

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